In the current state of the art, charts with multiple data sets graphed against a common axis (sometimes referred to as “multi-axis charts”) are typically limited to dual data sets per axis (e.g., representing two data sets on the vertical axis, commonly referred to as the “Y-axis”). Graphing two data sets against a common axis, such as the Y-axis, allows two graphs with different units to be displayed together in the same display area. Multi-axis charts of this type are rarely utilized, and when they are utilized the technology leaves configuration of many parameters used to display the chart up to the user on a case-by-case basis. For example, the value ranges represented on the common axis, the tick marks shown for each data, and the precision or step size shown for each data set are typically left to the chart designer to configure, often through cumbersome interfaces. Configuring the chart may involve long sets of dialogs requiring the designer to select a large number of different configuration options, view the resulting chart, and make adjustments until the display is acceptable.
Aligning the tick mark values for multiple data sets graphed against a common axis can be very challenging. Even if the chart designer manages to accomplish tick mark alignment for a particular chart size, the result is often less than optimal and limited to one particular display size, one particular set of data ranges, and one particular set of step sizes. Unfortunately, the painstakingly configured tick mark alignment of a carefully defined chart is often lost when a user changes the aspect ratio of the chart, accesses the chart with a different display device, or even when the user merely rotates or resizes the screen. Should the screen size or orientation, or the range values or step sizes change for any reason, the user must typically start over to realign the tick marks.
Conventional data charting systems offer little automation to optimize the presentation of multi-axis charts. In the dual axes case, automation may be employed to minimize the empty unused space, for example by adjusting the data ranges for each data set so that each graph fills the range space available along the common axis. Automatically adjusting the data ranges to eliminate unused space is typically accompanied by sacrificing the tick alignment between the data sets represented on the common axis. Showing non-aligned tick marks that are each represented by a horizontal line across the display area clutters the presentation.
Alternatively, the tick marks for one or more data sets may be recomputed so that they coincide to create common tick marks for multiple data sets graphed against a common axis, but this usually results in “off-round” tick marks with many place values rather than the more familiar “round” tick marks with fewer place values (e.g., the tick marks are presented with odd looking numbers with many place values, such as 176.567, instead of more easily understandable “round” figures with fewer place values, such as 175 or 180). In other words, adjusting the tick marks to numbers with many place values, as opposed to integer or “round” fractions with a small number of place values, impairs the tick value intuitiveness and reduces the readability and conceptual accessibility of the chart. This makes it more difficult for a reader to apprehend the relationships between the graphs at a glance, which is usually the purpose of representing multiple data sets with different units on a common axis in the first place. There is, therefore, a continuing need for a data visualization system with improved ability to graph multiple data sets against a common axis.